Senior ML Ops Engineer

Posted 23 Days Ago
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New York, NY, USA
In-Office
210K-300K Annually
Senior level
Financial Services
Build the AI operating system for the brands you see every day.
The Role
Own and build Confido's ML platform: design and operate end-to-end ML pipelines, infrastructure-as-code and CI/CD, optimize training/inference and agent workloads for latency/cost/throughput, integrate model data flows with data engineering, and ensure reliability, observability, security, and production model quality with online evals and human-in-the-loop review.
Summary Generated by Built In

Confido is the AI infrastructure powering modern CPG — the platform that 200+ brands like OLIPOP, Simple Mills, Dr. Squatch, and Tropicana use to run everything from deductions to production planning. Finance, accounting, sales, and operations, unified in one system for the first time.

We're growing 5x year over year and recently raised a $15M Series A led by Footwork and Y Combinator. We're a small, in-person team in New York City, which means the people who join now shape the product, the culture, and the company itself.

If you want your work on shelves everywhere — and outsized ownership while you build — we'd love to meet you.

The Role

Be the first dedicated owner of Confido's ML platform. Our AI/ML team already ships document-understanding, forecasting, and agentic systems into production — on infrastructure we've stood up by hand. You'll own that layer: the pipelines, serving, and cloud foundation that turn models and agents into reliable, cost-efficient production systems, at the scale of hundreds of thousands of documents and heavy LLM/VLM workloads.

Location: New York, NY (Relocation supported)


What you'll do
  • Own ML pipelines end to end — experimentation to production — and the infrastructure behind training, inference, and agentic workloads

  • Give the AI/ML team a paved road: reproducible environments and fast paths from prototype to production, so they can try new models and agents without fighting the infra

  • Stand up the cloud foundation as Infrastructure as Code and the CI/CD that ships ML safely

  • Serve and optimize inference and forecasting workloads — latency, throughput, and cost — and the data streams feeding them (e.g. turning a heavy synchronous model call into an async, parallelized one)

  • Own the data interface with data engineering: serve the right data to models and agents, and write their outputs back into the platform's data systems for the rest of Confido to use

  • Make reliability, observability, security, and privacy the default — and keep model and agent quality measurable in production through online evals and human-in-the-loop review, not just uptime


What we're looking for


Required

  • 5+ years in MLOps, ML platform, AI infrastructure, or platform engineering — on production ML systems, not pipelines on paper

  • You live at the seam of software and infrastructure: equally at home writing production code and standing up cloud infra.

  • You've driven a real pipeline end to end and can walk through it: the architecture, the security and cost trade-offs, and what you'd change

  • Deep cloud infrastructure understanding, distributed data systems, and IaC — you can boot an environment from scratch, wire CI/CD, and run containerized workloads in production without hand-holding

  • Strong Python and comfort in a production app codebase (Ruby, Java) monitoring, security, and cost are instincts, not afterthoughts

  • High ownership in a fast-moving startup, and experience productionizing what research/AI teams build

Nice to have

  • LLMOps tooling — tracing, prompt/version management, eval harnesses

  • Inference optimization (vLLM, ONNX, TensorRT) and GPU / spot-instance economics

  • ML platform and orchestration tooling (MLflow, BentoML, Ray, Airflow)

  • Large-scale data systems (Snowflake, Kafka) and vector databases

  • Managed ML services (Bedrock, SageMaker, Vertex AI)

  • Multimodal or generative AI in production

Our stack: Python · Ruby/Rails · AWS · Terraform · Kubernetes · GitHub Actions · Snowflake · Aurora/RDS · Redis · Kafka — with more of the above added as we scale.

Learn more about AI @ Confido here


🌴 Perks + Benefits
  • Equity — own a piece of what you're building

  • Fully paid health coverage with Aetna (we cover 100% of premiums)

  • Top-tier dental and vision through Guardian

  • 12 weeks paid parental leave

  • Unlimited PTO, plus regular 4-day holiday weekends we actually take

  • 401(k) through Vestwell

  • Paid relocation — we'll get you here

  • Full desk setup on day one (laptop, monitor, keyboard) + a $200 stipend to make it yours

  • Catered Friday lunches, team dinners on us, and unlimited coffee + snacks featuring our own brands

Confido provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Skills Required

  • 5+ years in MLOps, ML platform, AI infrastructure, or platform engineering on production ML systems
  • Proven end-to-end ownership of ML pipelines including architecture, security, and cost trade-offs
  • Strong Python and comfort working in production application codebases (Ruby, Java)
  • Deep cloud infrastructure understanding and distributed data systems; ability to boot environments from scratch and run containerized workloads
  • Infrastructure-as-Code experience (e.g., Terraform) and CI/CD for ML platforms
  • Experience with monitoring, security, cost optimization, and productionizing research/AI outputs
  • High ownership and ability to operate in a fast-moving startup environment

Confido Compensation & Benefits Highlights

  • Fair & Transparent Compensation Employer materials advertise top‑end pay positioning with clear salary bands on postings and a stated approach to setting salary and equity. Feedback suggests posted NYC ranges align with an upper‑tier startup pay philosophy.
  • Equity Value & Accessibility Compensation is framed to include meaningful equity, with transparent equity frameworks and visible bands on some roles. This positions ownership as a core part of total rewards rather than an add‑on.
  • Healthcare Strength Company‑paid medical plus dental and vision are highlighted across careers content and job posts, in some cases specifying employer‑covered premiums. This meaningfully reduces out‑of‑pocket costs for core coverage.

Confido Insights

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The Company
HQ: New York, NY
65 Employees
Year Founded: 2021

What We Do

CPG is a multi-trillion-dollar industry, but the path from factory to store shelf still runs on spreadsheets, emailed PDFs, and legacy systems held together with duct tape. Brands lose real time and money every day reconciling data, fighting retailer disputes, and coordinating across finance, sales, and supply chain. We're replacing that manual work with AI agents on a single intelligent platform — from cash application and deductions to demand forecasting, supply planning, and trade promotion management. It's working. We're the infrastructure behind 200+ brands, from OLIPOP to Simple Mills to Dr. Squatch, managing $40B+ in customer revenue, with 5x ARR growth. Backed by Footwork and Y Combinator.

Why Work With Us

You'll never wait for a performance review to get a raise or bonus you've earned. Ownership works the same way: trusted from day one to own things end to end. Need something to do your job better? You won't have to ask twice.

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Confido Offices

OnSite Workspace

We are on-site in Chelsea, New York.

Typical time on-site:
HQNew York Headquarters
Our company is in a trendy Chelsea neighborhood nearby plenty of restaurants, gyms, and bars.

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